I have pairs of EEG signals filtered to give me just alpha bands. For a machine learning problem I have found that calculating the phase locking value between the alpha signals of these 2 channels would be a useful classification feature.
I'm using this paper as a reference: http://www.ncbi.nlm.nih.gov/pubmed/22661936
I'm wondering what the correct method/implementation is to calculate PLV/synchrony in Python?
I have not been able to find any modules/code that would help me with this problem. That paper, for example, calculates synchrony between independent components after ICA, but I'm not employing that method here so not sure if their formula translates or if any adjustments are necessary for filtered signals
The closest thing I have found is this: https://www.nbtwiki.net/doku.php?id=tutorial:phase_locking_value#.VchjR6ZVhBc
However, while the code is laid out nearer the bottom of the page, it appears to be MATLAB code. It looks like there are some MATLAB methods being employed and I'm not sure how that would translate over to Python/numpy/scipy
I'm not particularly familiar with this domain and don't trust myself to port the code over without making logic errors, so it would be useful if someone could point me toward a Python implementation of this.